Clostridium difficile infection poses a clear and escalating threat to public health. Incidence and severity of disease are increasing,^1,2 and costs total more than $1 billion in the United States annually.³ Although other populations are at risk,⁴ most cases remain both nosocomial and iatrogenic.² Prevention is therefore paramount, but preventive measures have generally focused on isolation of infected patients, hand hygiene, and antibiotic stewardship.⁵

The objectives of this study were: 1) To determine the component needed to generate a validated DIC score during pregnancy. 2) To validate such scoring system in the identification of patients with clinical diagnosis of DIC. This is a population based retrospective study, including all women who gave birth at the ‘Soroka University Medical Center’ during the study period, and have had blood coagulation tests including complete blood cell count, prothrombin time (PT)(seconds), partial thromboplastin time (aPTT), fibrinogen, and D-dimers. Nomograms for pregnancy were established, and DIC score was constructed based on ROC curve analyses. 1) maternal plasma fibrinogen concentrations increased during pregnancy; 2) maternal platelet count decreased gradually during gestation; 3) the PT and PTT values did not change with advancing gestation; 4) PT difference had an area under the curve (AUC) of 0.96 (p<0.001), and a PT difference ≥1.55 had an 87% sensitivity and 90% specificity for the diagnosis of DIC; 5) the platelet count had an AUC of 0.87 (p<0.001), an 86% sensitivity and 71% specificity for the diagnosis of DIC; 6) fibrinogen concentrations had an AUC of 0.95 (p<0.001) and a cutoff point ≤3.9 g/L had a sensitivity of 87% and a specificity of 92% for the development of DIC; and 7) The pregnancy adjusted DIC score had an AUC of 0.975 (p<0.001) and at a cutoff point of ≥26 had a sensitivity of 88%, a specificity of 96%, a LR(+) of 22 and a LR(−) of 0.125 for the diagnosis of DIC. We could establish a sensitive and specific pregnancy adjusted DIC score. The positive likelihood ratio of this score suggests that a patient with a score of ≥26 has a high probability to have DIC.

To assess an association of Socio-economic status with utilization of health care services between years 2002 and 2008 in Israel. We retrospectively analyzed the utilization of health care services in a cohort of 100,000 members, 21 years and older, of a Clalit Health Services. The research compared utilization according to the neighborhood SES status; and clinic’s location as another SES proxy. Data included: Charlson Score morbidity factor, utilization of health care services (visits to primary physicians and specialists, purchase of pharmaceuticals, number of hospitalization days, visits to ED, utilization of laboratory tests and imaging). The analysis was performed using Generalized Linear Model (GLM) technique. People with lower SES visited more the ED and primary physicians and were hospitalized for longer periods. People with higher SES visited more specialists, bought more prescription drugs and used more medical imaging. The associations between SES and most of the services we analyzed did not change between 2002 and 2008. However, the gap between lower and higher SES levels in ED visits and the use of prescription drugs slightly increased over time, while the gap in visits to specialists decreased. The research shows that even in a universal health care system SES is associated with utilization of health care services. In order to improve equity in utilization of services the Israeli public health should reduce economic barriers and in parallel invest in making information accessible to improve “navigation skills” for all.

Rationale: Opioid abuse is increasing, but its impact on critical care resources in the United States is unknown. Objectives: We hypothesized that there would be a rising need for critical care among opioid-associated overdoses in the United States. Methods: We analyzed all adult admissions, using a retrospective cohort study from 162 hospitals in 44 states, discharged between January 1, 2009, and September 31, 2015 to describe the incidence of intensive care unit (ICU) admissions for opioid overdose during this time. Admissions were identified using the Clinical Database/Resource Manager of Vizient, the successor to the University Health System Consortium. Results: Our primary outcome was opioid-associated overdose admissions to the ICU. The outcome was defined on the basis of previously validated ICD-9 codes. Our secondary outcomes were in-hospital death and markers of ICU resources. The final cohort included 22,783,628 admissions; 4,145,068 required ICU care. There were 52.4 ICU admissions for overdose per 10,000 ICU admissions over the entire study (95% confidence interval [CI], 51.8–53.0 per 10,000 ICU admissions). During this time period, opioid overdose admissions requiring intensive care increased 34%, from 44 per 10,000 (95% CI, 43–46 per 10,000) to 59 per 10,000 ICU admissions (95% CI, 57–61 per 10,000; P < 0.0001). The mortality rate of patients with ICU admissions with overdoses averaged 7% (95% CI, 7.0–7.6%) but increased to 10% in 2015 (95% CI, 8.8–10.8%). Conclusions: The number of deaths of ICU patients with opioid overdoses increased substantially in the 7 years of our study, reflecting increases in both the incidence and mortality of this condition. Our findings raise the need for a national approach to developing safe strategies to care for patients with overdose in the ICU, to providing coordinated resources in the hospital for patients and families, and to helping survivors maintain sobriety on discharge.